{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I ran the following notebook in a docker container with the following commands:\n",
    "\n",
    "```\n",
    "docker pull bethgelab/jupyter-torch:ubuntu-14.04\n",
    "docker run -it -v `pwd`:/space/ -p 8888:8888 --name keras -w /space/ --rm bethgelab/jupyter-torch:ubuntu-14.04 jupyter notebook --ip=0.0.0.0\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following code is adapted from https://github.com/fastforwardlabs/keras-hello-world/blob/master/kerashelloworld.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/IPython/html.py:14: ShimWarning: The `IPython.html` package has been deprecated. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.\n",
      "  \"`IPython.html.widgets` has moved to `ipywidgets`.\", ShimWarning)\n",
      "Using Theano backend.\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from sklearn.linear_model import LogisticRegressionCV\n",
    "\n",
    "from keras.models import Sequential\n",
    "from keras.layers.core import Dense, Activation\n",
    "from keras.utils import np_utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length  sepal_width  petal_length  petal_width species\n",
       "0           5.1          3.5           1.4          0.2  setosa\n",
       "1           4.9          3.0           1.4          0.2  setosa\n",
       "2           4.7          3.2           1.3          0.2  setosa\n",
       "3           4.6          3.1           1.5          0.2  setosa\n",
       "4           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris = sns.load_dataset(\"iris\")\n",
    "iris.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/matplotlib/font_manager.py:1314: UserWarning: findfont: Font family [u'sans-serif'] not found. Falling back to DejaVu Sans\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
      "image/png": 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NazpMl+JCq+D2uposBl2dQjcSshSIRIkWKmWo6Lx8o2NXUNnW2qm4cKc4fj5c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\nn0j/KK07Noanrw6dc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zhLqPl0QK581VqqVTuv3N02LhRJRJQ4ueAy4QE8pIY/sX0mPUp6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\nSi5VXzKnvuwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc27c155490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(iris, hue='species');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X = iris.values[:, :4]\n",
    "y = iris.values[:, 4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train_X, test_X, train_y, test_y = train_test_split(X, y, train_size=0.5, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegressionCV(Cs=10, class_weight=None, cv=None, dual=False,\n",
       "           fit_intercept=True, intercept_scaling=1.0, max_iter=100,\n",
       "           multi_class='ovr', n_jobs=1, penalty='l2', random_state=None,\n",
       "           refit=True, scoring=None, solver='lbfgs', tol=0.0001, verbose=0)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr = LogisticRegressionCV()\n",
    "lr.fit(train_X, train_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy = 0.83\n"
     ]
    }
   ],
   "source": [
    "print(\"Accuracy = {:.2f}\".format(lr.score(test_X, test_y)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def one_hot_encode_object_array(arr):\n",
    "    '''One hot encode a numpy array of objects (e.g. strings)'''\n",
    "    uniques, ids = np.unique(arr, return_inverse=True)\n",
    "    return np_utils.to_categorical(ids, len(uniques))\n",
    "\n",
    "train_y_ohe = one_hot_encode_object_array(train_y)\n",
    "test_y_ohe = one_hot_encode_object_array(test_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from keras.layers.core import Dropout"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = Sequential()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.add(Dense(16, input_shape=(4,)))\n",
    "model.add(Activation('sigmoid'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.add(Dense(3))\n",
    "model.add(Dropout(0.01))\n",
    "model.add(Activation('softmax'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy = 0.97\n"
     ]
    }
   ],
   "source": [
    "model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=[\"accuracy\"])\n",
    "model.fit(train_X, train_y_ohe, nb_epoch=1000, batch_size=1, verbose=0)\n",
    "loss, accuracy = model.evaluate(test_X, test_y_ohe, verbose=0)\n",
    "print(\"Accuracy = {:.2f}\".format(accuracy))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
